Camera Pose Filtering with Local Regression Geodesics on the Riemannian Manifold of Dual Quaternions

Benjamin Busam, Tolga Birdal, Nassir Navab

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

20 Zitate (Scopus)

Abstract

Time-varying, smooth trajectory estimation is of great interest to the vision community for accurate and well behaving 3D systems. In this paper, we propose a novel principal component local regression filter acting directly on the Riemannian manifold of unit dual quaternions DH1. We use a numerically stable Lie algebra of the dual quaternions together with exp and log operators to locally linearize the 6D pose space. Unlike state of the art path smoothing methods which either operate on SO (3) of rotation matrices or the hypersphere H1 of quaternions, we treat the orientation and translation jointly on the dual quaternion quadric in the 7-dimensional real projective space RP7. We provide an outlier-robust IRLS algorithm for generic pose filtering exploiting this manifold structure. Besides our theoretical analysis, our experiments on synthetic and real data show the practical advantages of the manifold aware filtering on pose tracking and smoothing.

OriginalspracheEnglisch
TitelProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten2436-2445
Seitenumfang10
ISBN (elektronisch)9781538610343
DOIs
PublikationsstatusVeröffentlicht - 1 Juli 2017
Veranstaltung16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 - Venice, Italien
Dauer: 22 Okt. 201729 Okt. 2017

Publikationsreihe

NameProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Band2018-January

Konferenz

Konferenz16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Land/GebietItalien
OrtVenice
Zeitraum22/10/1729/10/17

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